Process reports

Here we process reports by identifying specific character names in each sentence to account for character-specific sentiment analysis. We’ll examine over general storylines (across all chapters) and chapter-by-chapter karmic balance.

As for the overall team karma, using afinn lexicon, score each report over time using a cumulative sum. The reports all trend downward using raw scores, indicating an overall negative tone. To help account for this, there is a pos_adj parameter that calculates the ratio of abs(sum(neg) / sum(pos)). Multiplying the positive scores by (some fraction of) this parameter helps boost those scores in relation to negative scores.

Plot character storylines

For each character, chart out the cumulative sum of ‘karmic balance’ - using word count as a metric of time. This is averaged over all adventures to estimate the general character ethos - how they approach a mission.

Plot karmic balance by chapter

A bar chart showing the karmic balance of each character for each chapter - resulting in a general character arc over the campaign.